Neural network control for earthquake structural vibration reduction using MRD

Khaled Zizouni1, Leyla Fali2, Younes Sadek2, Ismail Khalil Bousserhane1,3
1ArcihPEL Laboratory, University TAHRI Mohammed, Bechar, Algeria
2FIMAS Laboratory, University TAHRI Mohammed, Bechar, Algeria
3Laboratory of Smart-Grid and Renewable Energies, University TAHRI Mohammed, Bechar, Algeria

Tóm tắt

Structural safety of building particularly that are intended for exposure to strong earthquake loads are designed and equipped with high technologies of control to ensure as possible as its protection against this brutal load. One of these technologies used in the protection of structures is the semi-active control using a Magneto Rheological Damper device. But this device need an adequate controller with a robust algorithm of current or tension adjustment to operate which is further discussed in the following of this paper. In this study, a neural network controller is proposed to control the MR damper to eliminate vibrations of 3-story scaled structure exposed to Tōhoku 2011 and Boumerdès 2003 earthquakes. The proposed controller is derived from a linear quadratic controller designed to control an MR damper installed in the first floor of the structure. Equipped with a feedback law the proposed control is coupled to a clipped optimal algorithm to adapt the current tension required to the MR damper adjustment. To evaluate the performance control of the proposed design controller, two numerical simulations of the controlled structure and uncontrolled structure are illustrated and compared.

Tài liệu tham khảo

Cherkaoui T, Medina F, Hatzfeld D. The Agadir earthquake of February 29, 1960, examination of some of the parameters. Monografia of Instituto Geografico Nacional, 1991, 8: 133–148 Buckle I G. Passive control of structures for seismic loads. In: Proceeding of the 12th World Conference on Earthquake Engineering. Auckland, 2000 Riascos C, Casas J M, Thomson P. Semi-active tuned liquid column damper implementation with real-time hybrid simulations. In: Proceeding SPIE, Active and Passive Smart Structures and Integrated Systems. Nevada, 2016, 1–9 Fisco N R, Adeli H. Smart structures: Part I-Active and semi-active control. Scientia Iranica, 2011, 18(3): 275–284 Dyke S J, Spencer B F, Sain M K, Carlson J D. Experimental verification of semi-active structural control strategies using acceleration feedback. In: Proceeding of the 3rd International Conference on Motion and Vibration Control. Chiba, 1996, 3: 291–296 Yao J T P. Concept of structural control. Journal of the Structural Division, 1972, 98(7): 1567–1574 Luca S G, Chira F, Rosea V O. Passive, active and semi-active control systems in civil engineering. Bulletin of the Polytechnic Institute of Jassy, Constructions. Architecture Section, 2005, 3-4: 23–31 Cancellara D, Pasquino M. A new passive seismic control device for protection of structures under anomalous seismic events. Applied Mechanics and Materials, 2011, 82: 651–656 Abreu G L C M, Lopes V Jr, Brennan M J. Robust control of a two-floors building model using active mass driver. In: Proceeding of ISMA2010 Including USD2010, 2012, 215–226 Abdel-Rohman M. Optimal design of active TMD for buildings control. Building and Environment, 1984, 19(3): 191–195 Battaini M, Casciati F, Faravelli L. Fuzzy control of structural vibration: An active mass system driven by a fuzzy controller. Earthquake Engineering & Structural Dynamics, 1998, 27(11): 1267–1276 Dyke S J, Spencer B F. A comparison of semi-active control strategies for the MR damper. In: Proceedings of the LASTED International Conference, Intelligent Information Systems. The Bahamas, 1997 Carlson J D. What makes a good MR fluid? Journal of Intelligent Material Systems and Structures, 2002, 13(7–8): 431–435 Oliveira F, Botto M A, Morais P, Suleman A. Semi-active structural vibration control of base-isolated buildings using magnetorheological dampers. Journal of Low Frequency Noise, Vibration and Active Control, 2017, 37(3): 565–576 Yoshida O, Dyke S J, Giacosa L M, Truman K Z. Experimental verification of torsional response control of asymmetric buildings using MR dampers. Earthquake Engineering & Structural Dynamics, 2003, 32(13): 2085–2105 Casciati F, Rodellar J, Yildirim U. Active and semi-active control of structures - theory and applications: A review of recent advances. Journal of Intelligent Material Systems and Structures, 2012, 23(11): 1181–1195 Hamdia K M, Silani M, Zhuang X, He P, Rabczuk T. Stochastic analysis of the fracture toughness of polymeric nanoparticle composites using polynomial chaos expansions. International Journal of Fracture, 2017, 206(2): 215–227 Hamdia K M, Lahmer T, Nguyen-Thoi T, Rabczuk T. Predicting the fracture toughness of PNCs: A stochastic approach based on ANN and ANFIS. Computational Materials Science, 2015, 102: 304–313 Pajchrowski T, Zawirski K. Application of artificial neural network to robust speed control of servodrive. IEEE Transactions on Industrial Electronics, 2007, 54(1): 200–207 Maiti S, Verma V, Chakraborty C, Hori Y. An adaptive speed sensorless induction motor drive with artificial neural network for stability enhancement. IEEE Transactions on Industrial Informatics, 2012, 8(4): 757–766 Zizouni K, Bousserhane I K, Hamouine A, Fali L M R. Damper-LQR control for earthquake vibration mitigation. International Journal of Civil Engineering and Technology, 2017, 8(11): 201–207 Liu X, Wu Y, Zhang Y, Xiao S. A control method to make LQR robust: A planes cluster approaching mode. International Journal of Control, Automation, and Systems, 2014, 12(2): 302–308 Montazeri A, Poshtan J, Choobdar A. Performance and robust stability trade-off in minimax LQG control of vibrations in flexible structures. Engineering Structures, 2009, 31(10): 2407–2413 Neelakantan V A, Washington G N. Vibration control of structural systems using MR dampers and a ‘Modified’ sliding mode control technique. Journal of Intelligent Material Systems and Structures, 2008, 19(2): 211–224 Aldawod M, Samali B, Naghdy F, Kwok K C S. Active control of along wind response of tall building using a fuzzy controller. Engineering Structures, 2001, 23(11): 1512–1522 Heidari A H, Etedali S, Javaheri-Tafti M R. A hybrid LQR-PID control design for seismic control of buildings equipped with ATMD. Frontiers of Structural and Civil Engineering, 2018, 12(1): 44–57 Schurter K C, Roschke P N. Neuro-Fuzzy control of structures using magnetorheological dampers. In: Proceedings of the American control conference. Arlington, Virginia, 2001, 1097–1102 Jansen L M, Dyke S J. Semi-active control strategies for MR dampers: A comparative study. Journal of Engineering Mechanics, 2000, 126(8): 795–803 Pohoryles D A, Duffour P. Adaptive control of structures under dynamic excitation using magnetorheological dampers: An improved clipped-optimal control algorithm. Journal of Vibration and Control, 2015, 21(13): 2569–2582 Bingham E C. An investigation of the laws of plastic flow. U.S. Bureau of Standards Bulletin, 1916, 13(2): 309–353 Gamota D R, Filisko F E. Dynamic mechanical studies of electrorheological materials: Moderate frequencies. Journal of Rheology (New York, N.Y.), 1991, 35(3): 399–425 Ismail M, Ikhouane F, Rodellar J. The hysteresis Bouc-Wen model, a survey. Archives of Computational Methods in Engineering, 2009, 16(2): 161–188 Spencer B F Jr, Dyke S J, Sain M K, Carlson J D. Phenomenological model for Magneto-Rheological dampers. Journal of Engineering Mechanics, 1997, 123(3): 230–238 Naidu D S. Optimal Control Systems. Special Indian ed. FL: CRC Press, 2002 Liu X, Wu Y, Zhang Y, Xiao S. A control method to make LQR robust: A planes cluster approaching mode. International Journal of Control, Automation, and Systems, 2014, 12(2): 302–308 Barnett S, Storey C. Some results on the sensitivity and synthesis of asymptotically stable linear and non-linear systems. Automatica, 1968, 4(4): 187–194 Lancaster P, Rodman L. Algebraic Riccati Equations. Oxford: Oxford University Press, 1995 Vu-Bac N, Lahmer T, Zhuang X, Nguyen-Thoi T, Rabczuk T. A software framework for probabilistic sensitivity analysis for computationally expensive models. Advances in Engineering Software, 2016, 100: 19–31 Cui X, Shin K G. Direct control and coordination using neural networks. IEEE Transactions on Systems, Man, and Cybernetics, 1993, 23(3): 686–697 Rabiee A H, Markazi A H D. Semi-active adaptive fuzzy sliding mode control of buildings under earthquake excitations. In: Proceedings of the 2nd World Congress on Civil, Structural, and Environmental Engineering. Barcelona, Spain, 2017 Dyke S J, Spencer B F Jr, Sain M K, Carlson J D. Modeling and control of magnetorheological dampers for seismic response reduction. Smart Materials and Structures, 1996, 5(5): 565–575